Bai Chang

509 total citations
23 papers, 341 citations indexed

About

Bai Chang is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Rehabilitation. According to data from OpenAlex, Bai Chang has authored 23 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Endocrinology, Diabetes and Metabolism, 7 papers in Molecular Biology and 4 papers in Rehabilitation. Recurrent topics in Bai Chang's work include Diabetic Foot Ulcer Assessment and Management (4 papers), Wound Healing and Treatments (4 papers) and Pressure Ulcer Prevention and Management (3 papers). Bai Chang is often cited by papers focused on Diabetic Foot Ulcer Assessment and Management (4 papers), Wound Healing and Treatments (4 papers) and Pressure Ulcer Prevention and Management (3 papers). Bai Chang collaborates with scholars based in China. Bai Chang's co-authors include Juhong Yang, Miaoyan Zheng, Jingyu Wang, Xiaochen Li, Jing Li, Yuan Wang, Wenhui Jiang, Wenli Lu, Ran Liu and Xiaofang Shen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Diabetes Care and Thrombosis and Haemostasis.

In The Last Decade

Bai Chang

22 papers receiving 336 citations

Peers

Bai Chang

EDM

NEPHR

SURGE

CCM

MM Suchitra India

Agnieszka Ćwiklińska Poland

Agnieszka Kuchta Poland

Tayyibe Saler Türkiye

Monia Garofolo Italy

Xisheng Xie China

Khedidja Mekki Algeria

R.-M. Schmülling Germany

Bingxuan Zhang China

H. Grassos Greece

MM Suchitra India

Bai Chang

127 ×1.0

EDM

56 ×0.7

NEPHR

71 ×1.0

31 ×0.8

SURGE

33 ×0.8

CCM

Citations per year, relative to Bai Chang Bai Chang (= 1×) peers MM Suchitra

Countries citing papers authored by Bai Chang

Since Specialization

Citations

This map shows the geographic impact of Bai Chang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bai Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bai Chang more than expected).

Fields of papers citing papers by Bai Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bai Chang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bai Chang. The network helps show where Bai Chang may publish in the future.

Co-authorship network of co-authors of Bai Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Bai Chang. A scholar is included among the top collaborators of Bai Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bai Chang. Bai Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chen, Weiling, et al.. (2023). Most postoperative reserved “normal” metatarsal stumps of diabetic foot osteomyelitis are infected but have healing potential. Frontiers in Endocrinology. 14. 1165305–1165305.

Chen, Dong, et al.. (2022). Risk Factors for Multidrug-Resistant Organisms Infection in Diabetic Foot Ulcer. SHILAP Revista de lepidopterología. 12 indexed citations

Zhang, Jinghang, et al.. (2022). The association between estimated glomerular filtration rate and prognosis in patients with diabetic foot osteomyelitis. International Wound Journal. 19(7). 1650–1657. 3 indexed citations

Chen, Dong, Meijun Wang, Xin Shang, et al.. (2021). Development and validation of an incidence risk prediction model for early foot ulcer in diabetes based on a high evidence systematic review and meta-analysis. Diabetes Research and Clinical Practice. 180. 109040–109040. 33 indexed citations

B, Ma, et al.. (2020). EGLIF-CAR-T Cells Secreting PD-1 Blocking Antibodies Significantly Mediate the Elimination of Gastric Cancer. SHILAP Revista de lepidopterología. 3 indexed citations

Zhou, Shengnan, et al.. (2020). Early intervention with Di-Dang Decoction prevents macrovascular fibrosis in diabetic rats by regulating the TGF-β1/Smad signalling pathway. Chinese Journal of Natural Medicines. 18(8). 612–619. 4 indexed citations

Jiang, Wenhui, Jingyu Wang, Xiaofang Shen, et al.. (2020). Establishment and Validation of a Risk Prediction Model for Early Diabetic Kidney Disease Based on a Systematic Review and Meta-Analysis of 20 Cohorts. Diabetes Care. 43(4). 925–933. 129 indexed citations

Han, Fei, Xiaochen Li, Juhong Yang, et al.. (2019). Salsalate Prevents β-Cell Dedifferentiation in OLETF Rats with Type 2 Diabetes through Notch1 Pathway. Aging and Disease. 10(4). 719–719. 14 indexed citations

Yang, Shaohua, Juhong Yang, Miaoyan Zheng, et al.. (2019). Hyperinsulinemia Can Cause Kidney Disease in the IGT Stage of OLETF Rats via the INS/IRS-1/PI3-K/Akt Signaling Pathway. Journal of Diabetes Research. 2019. 1–12. 13 indexed citations

10.

Wang, Jingyu, Chunyan Shan, Yi Zhang, et al.. (2017). Characteristics and Impact Factors of Renal Threshold for Glucose Excretion in Patients with Type 2 Diabetes Mellitus. Journal of Korean Medical Science. 32(4). 621–621. 13 indexed citations

11.

Li, Jing, et al.. (2017). Early intervention with Didang decoction delays macrovascular lesions in diabetic rats through regulating AMP-activated protein kinase signaling pathway. Chinese Journal of Natural Medicines. 15(11). 847–854. 11 indexed citations

12.

Li, Jing, et al.. (2016). Early Intervention of Didang Decoction on MLCK Signaling Pathways in Vascular Endothelial Cells of Type 2 Diabetic Rats. International Journal of Endocrinology. 2016. 1–7. 5 indexed citations

13.

Yang, Juhong, Miaoyan Zheng, Yan Wang, et al.. (2015). Clinical Characteristics and Predictive Factors of Subclinical Diabetic Nephropathy. Experimental and Clinical Endocrinology & Diabetes. 123(2). 132–138. 12 indexed citations

14.

Zhong, Zhen, Bai Chang, Min Li, et al.. (2011). Anti-Diabetic Effects of aCoptis chinensisContaining New Traditional Chinese Medicine Formula in Type 2 Diabetic Rats. The American Journal of Chinese Medicine. 39(1). 53–63. 48 indexed citations

15.

Li, Min, et al.. (2011). Hepatic PTP1B Expression Involvement in the Effects of Chinese Medicine Formula Xiao-Gao-Jiang-Zhuo Using an Obese Rat Model. The American Journal of Chinese Medicine. 39(2). 301–313. 5 indexed citations

16.

Chang, Bai, Zhen Zhong, Yi Zhai, et al.. (2009). Lowering blood sugar of obese patients with type 2 diabetes by only using dispersing stagnation and clearing heat therapy for a long term.. Zhonghua zhongyiyao zazhi. 24(2). 132–134. 2 indexed citations

17.

Zhong, Zhen, et al.. (2009). Influence of Kaiyuqingre Formula on glycolipin metabolism in spontaneous obese T2DM rats.. Zhonghua zhongyiyao zazhi. 24(8). 1056–1058. 2 indexed citations

18.

Tong, Xiaolin, et al.. (2009). New discussion of Pi-dan.. Zhonghua zhongyiyao zazhi. 24(8). 988–991. 3 indexed citations

19.

Ma, Shuiqing, Bai Chang, & Xiangbing Bian. (2001). Investigation of thrombomodulin and plasminogen activator inhibitor type-I in pregnancy induced hypertension and its clinical significance.. PubMed. 16(3). 169–71. 3 indexed citations

20.

Ma, Shuiqing, Bai Chang, & Xiangbing Bian. (1999). [Study on thrombomodulin and plasminogen activator inhibitor type-1 in patients of pregnancy induced hypertension].. PubMed. 34(12). 712–4. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact